enhancement

[RuhanikaChotwani]

Describe your change:

✅ Add an algorithm

Description:

Added Linear Regression implementations:

Naive implementation using loops for beginners to understand step by step.

Fully vectorized implementation using NumPy for faster and scalable computation.

Includes a test case to verify that both implementations produce similar results.

Added type hints, docstrings, and reference links to Linear Regression concepts for clarity.

Resolves issue #13205(#13205)

• This pull request is all my own work -- I have not plagiarized.

• I know that pull requests will not be merged if they fail the automated tests.

• This PR only changes one algorithm file.

• All new Python files are placed inside an existing directory.

• All filenames are in all lowercase characters with no spaces or dashes.

• All functions and variable names follow Python naming conventions.

• All function parameters and return values are annotated with Python.

• All functions have doctests
  that pass the automated testing.

• Checklist:

• I have read CONTRIBUTING.md.

• This pull request is all my own work -- I have not plagiarized.

• I know that pull requests will not be merged if they fail the automated tests.

• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.

• All new Python files are placed inside an existing directory.

• All filenames are in all lowercase characters with no spaces or dashes.

• All functions and variable names follow Python naming conventions.

• All function parameters and return values are annotated with Python type hints.

• All functions have doctests that pass the automated testing.

• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.

• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-Upgrade Linear Regression with Fully Vectorized Implementation and add a naive implementation for beginners #13205"

[algorithms-keeper]

Closing this pull request as invalid

@RuhanikaChotwani, this pull request is being closed as none of the checkboxes have been marked. It is important that you go through the checklist and mark the ones relevant to this pull request. Please read the Contributing guidelines.

If you're facing any problem on how to mark a checkbox, please read the following instructions:

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• If it is, then mark it by putting a x between the square bracket like so: [x]

NOTE: Only [x] is supported so if you have put any other letter or symbol between the brackets, that will be marked as invalid. If that is the case then please open a new pull request with the appropriate changes.

[algorithms-keeper]

Click here to look at the relevant links ⬇️

🔗 Relevant Links

Repository:

• Contributing guidelines
• Project Euler solution guidelines

Python:

• Formatted string literals (f-strings)
• Type hints
• doctest
• unittest
• pytest

Automated review generated by algorithms-keeper. If there's any problem regarding this review, please open an issue about it.

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[algorithms-keeper]

As there is no test file in this pull request nor any test function or class in the file machine_learning/01_linear_regression.py, please provide doctest for the function naive_linear_regression

Please provide descriptive name for the parameter: X

Please provide descriptive name for the parameter: y

Please provide return type hint for the function: naive_linear_regression. If the function does not return a value, please provide the type hint as: def function() -> None:

Please provide type hint for the parameter: X

Please provide type hint for the parameter: y

Please provide type hint for the parameter: learning_rate

Please provide type hint for the parameter: epochs

[algorithms-keeper]

As there is no test file in this pull request nor any test function or class in the file machine_learning/01_linear_regression.py, please provide doctest for the function vectorized_linear_regression

Please provide descriptive name for the parameter: X

Please provide descriptive name for the parameter: y

Please provide return type hint for the function: vectorized_linear_regression. If the function does not return a value, please provide the type hint as: def function() -> None:

Please provide type hint for the parameter: X

Please provide type hint for the parameter: y

Please provide type hint for the parameter: learning_rate

Please provide type hint for the parameter: epochs